PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1927686
PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1927686
Quantum computing in life sciences market size was valued at US$ 201.21 Million in 2024, expanding at a CAGR of 39.12% from 2025 to 2032.
Quantum computing in life sciences refers to the application of quantum algorithms and quantum hardware to solve complex biological and medical problems that are computationally impractical for classical systems, including molecular simulations, genomics analysis, and drug discovery. The market is emerging alongside strong public-sector R&D investment in quantum technologies and biomedical research. According to the U.S. National Science Foundation (NSF), federal funding for quantum information science exceeded USD 1.2 billion annually under the National Quantum Initiative. In parallel, the U.S. National Institutes of Health (NIH) allocated over USD 47 billion in 2023 to biomedical research, creating a strong foundation for integrating quantum computing into life sciences workflows. Opportunities lie in high-accuracy molecular modeling, accelerated drug discovery pipelines, and precision medicine applications supported by government-backed research ecosystems.
Quantum Computing in Life Sciences Market- Market Dynamics
Rising government-backed drug discovery modernization and genomics-scale data growth to drive market demand
National governments are accelerating adoption of advanced computing in life sciences to address the growing computational burden of drug discovery and precision medicine. The U.S. Food and Drug Administration (FDA) reports that over 90% of drug candidates fail during clinical development, highlighting the need for faster molecular modeling, target screening, and trial optimization methods. Meanwhile, the U.S. National Library of Medicine (NIH) hosts over 40 petabytes of biomedical and genomic data, a scale increasingly impractical for classical computing alone. Public genomics initiatives, population health programs, and national biopharma competitiveness strategies are driving interest in quantum-enabled simulation and optimization. In parallel, government-funded quantum testbeds and healthcare AI programs across North America, Europe, and Asia are encouraging early integration of quantum workflows into molecular modeling, protein folding, and clinical research pipelines, supporting long-term commercialization potential.
The Global Quantum Computing in Life Sciences Market is segmented on the basis of Deployment Mode, Application, Technology, End User, and Region.
Based on Application, the market is segmented into Drug Discovery & Development, Genomics & Precision Medicine, Molecular Modelling & Simulation, Drug Repurposing, Protein Folding, Biomarker Discovery, and Clinical Trial Optimization. Drug discovery-related use cases are the most significant to watch, as quantum algorithms are increasingly explored to model molecular interactions beyond classical computing limits. According to the U.S. National Institutes of Health (NIH), federal funding for computational biology and bioinformatics exceeded USD 1.7 billion in FY2023, reflecting growing emphasis on advanced computing methods to accelerate therapeutic development. Genomics and precision medicine applications are also gaining traction as public health agencies expand large-scale sequencing and population health programs requiring complex data analysis.
Based on Technology, the market is categorized into Gate-based Quantum Computing (including superconducting, trapped-ion, photonic, and topological qubits), Quantum Simulation, Quantum Annealing, and Analog Quantum Computing. Gate-based systems are the primary focus of government-backed research due to their flexibility in running complex life-science algorithms. The U.S. Department of Energy (DOE) reports that its national laboratories are actively deploying gate-based and quantum simulation platforms under the National Quantum Initiative to support chemistry, biology, and materials research. Quantum annealing remains relevant for optimization problems such as molecular conformations and clinical trial design, while analog quantum systems are explored for specialized biochemical simulations in early-stage research environments.
Quantum Computing in Life Sciences Market- Geographical Insights
The global quantum computing in life sciences market shows clear regional variation shaped by public R&D funding, national quantum strategies, and biomedical research intensity. North America is expected to hold the major market share, supported by strong government backing for quantum and life sciences research; under the U.S. National Quantum Initiative, federal agencies have committed over USD 3.7 billion during 2019-2024 to advance quantum technologies across healthcare, chemistry, and biology applications. Europe follows, driven by coordinated research programs such as Horizon Europe, where the European Commission has allocated EUR 1 billion to quantum technologies, with life sciences and pharmaceutical modelling identified as priority domains. Asia-Pacific is projected to grow at the fastest rate, supported by expanding public investment in quantum R&D and genomics programs in China, Japan, and South Korea. Meanwhile, Latin America, the Middle East, and Africa are gradually emerging as adoption centers, supported by academic collaborations, national digital health initiatives, and growing participation in international quantum research networks.
U.S. Quantum Computing in Life Sciences Market- Country Insights
The United States leads global adoption of quantum computing within life sciences due to its mature biomedical research ecosystem, early-stage quantum infrastructure, and strong coordination between public research institutions and technology developers. Federal research programs actively promote quantum-enabled advancements in molecular simulation, drug discovery, and genomics through national laboratories and university-led initiatives. The country benefits from close collaboration between life sciences researchers, pharmaceutical innovators, and quantum hardware and software developers, accelerating real-world experimentation and validation. A strong regulatory framework, deep talent pool, and sustained public-sector involvement in advanced computing research reinforce the U.S. position as the primary innovation hub for quantum applications in life sciences.
Rising computational complexity in molecular biology and drug research is intensifying competition across the quantum computing ecosystem supporting life sciences applications. Key players include IBM, Google Quantum AI, Microsoft, Quantinuum, IonQ, Rigetti Computing, D-Wave Systems, and Fujitsu. These companies focus on advancing qubit stability, hybrid quantum-classical workflows, and cloud-based access for pharmaceutical and biotech users. Common strategies include partnerships with drug discovery firms and research institutes, co-development of quantum algorithms for chemistry and genomics, and integration with high-performance computing platforms. Players are also investing heavily in software toolkits, developer ecosystems, and pilot programs to transition quantum use cases from experimental research to early-stage commercial adoption.
In November 2025, Quantinuum commercially launched its new Helios quantum computer, delivering unprecedented computational accuracy to support generative quantum AI (GenQAI) workflows. Helios enhances precision for complex simulations and algorithm training, enabling life sciences and other industries to accelerate discovery, optimization, and predictive modeling with improved performance and reduced error rates compared to prior systems.
In August 2025, Polaris Quantum Biotech launched QuADD, a quantum-AI drug discovery platform combining quantum annealing and artificial intelligence to explore vast chemical spaces (up to 103° theoretical molecules) and generate optimized candidate libraries in hours. The company is inviting researchers, biotech firms, and academic teams to join its beta testing program for early access and real-world evaluation of the system.